10 papers
Design Space Exploration of Reinforcement Learning Configurations for Post-Legalization Placement
Foteini Oikonomou, Maria Pantazi-Kypraiou, George Goudroumanis +5
Graph Neural Networks (GNNs) and Reinforcement Learning (RL) have recently been explored for VLSI placement optimization, but their effectiveness for post-legalization placement re…
A Pipelined FPGA Architecture for Banded Sparse Matrix Dense Matrix Multiplication in Longformer
Phillip Pramberger, Athanasios Tziouvaras, Shreejith Shanker +1
Sparse attention mechanisms have become increasingly important for transformer models processing long input sequences due to their lower computational and memory complexity compare…
GPlaceRL: An Open-Source Graph Reinforcement Learning Framework for Detailed Placement
Pavlos Stoikos, Foteini Oikonomou, Christos Poulos +5
Reinforcement learning (RL) has emerged as a promising approach for placement optimization, particularly when combined with graph neural networks (GNNs) that capture circuit connec…
Reinforcement Learning-Based Optimization of Workload-Aware Power Delivery Networks
Oran Hayes, Maria Pantazi-Kypraiou, Athanasios Tziouvaras +4
Power Delivery Networks (PDNs) are critical components of modern VLSI chips, providing stable voltage levels while satisfying electromigration (EM) and IR-drop constraints. Convent…
Constrained Bayesian Optimization for Hierarchical Federated Learning in IoT Networks for Plant Disease Classification
Athanasios Papanikolaou, Athanasios Tziouvaras, Apostolos Xenakis +6
The deployment of Hierarchical Federated Learning (HFL) in resource-constrained Internet of Things (IoT) environments requires careful configuration to balance predictive performan…
Workload-Aware Early-Stage Power Delivery Network Optimization via Architectural Power Traces
Oran Hayes, Maria Pantazi-Kypraiou, Athanasios Tziouvaras +4
Power Delivery Networks (PDNs) are critical for maintaining voltage integrity in modern multiprocessor systems. Conventional early-stage PDN planning relies on static or worst-case…
Performance and Energy Trade-Off Analysis of Hierarchical Federated Learning for Plant Disease Classification
Athanasios Papanikolaou, Athanasios Tziouvaras, Pavlos Stoikos +6
Early detection of plant diseases is critical for improving crop productivity, while it also facilitates the foundations of precision agriculture. Recent advances in distributed de…
Multi-Partner Project: COIN-3D -- Collaborative Innovation in 3D VLSI Reliability
George Rafael Gourdoumanis, Fotoini Oikonomou, Maria Pantazi-Kypraiou +10
As semiconductor manufacturing advances from the 3-nm process toward the sub-nanometer regime and transitions from FinFETs to gate-all-around field-effect transistors (GAAFETs), th…
Label-Free Concept Drift Assessment for Reliable AI in Emerging Wireless Applications
Athanasios Tziouvaras, Carolina Fortuna, George Floros +4
Machine learning models deployed in non-stationary environments degrade silently, since as the input distribution drifts their accuracy decays without an error signal and without l…
A Representation Learning Approach to Feature Drift Detection in Wireless Networks
Athanasios Tziouvaras, Blaz Bertalanic, George Floros +3
AI is foreseen to be a centerpiece in next generation wireless networks enabling enabling ubiquitous communication as well as new services. However, in real deployment, feature dis…